https://doi.org/10.31648/aspal.4608
The paper contains the comparison of mechanism of two separately constructed statistical methods for the detection of outliers in real estate market analysis. For this purpose, databases with various types of real estate from local markets were created. Then the estimation of parameters of functional models describing dependencies prevailing on the examined markets was carried out. Subsequently, statistical tools called Baarda’s method and model residual analysis were used to detect outliers in the collected datasets. The last stage was a comparison of the obtained results of the parameters’ estimation of the analyzed models and the measures of their quality, before and after the removal of outliers. The obtained results indicate that algorithms of chosen statistical methods, detecting outliers, allow to eliminate a smaller number of them, at the same time obtaining an improvement of the parameters of the functional model and its adjustment to the analyzed dataset. Therefore the conclusion is that a simple statistical method, which is the study of the occurrence of cases deviating from the functional model based on the analysis of residues can generate the same results as the use of a much more complicated algorithm as the one proposed by Baarda.
Download files
Citation rules
Licence
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
English
